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Record W4383502181 · doi:10.4050/f-0079-2023-17978

Full-Aircraft CH-53K® Hover Simulations with Helios

2023· article· en· W4383502181 on OpenAlexaff
В.Й. Климченко, Byung-Young Min, Jinggen Zhao, Brian Wake, Jeewoong Kim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsFuselageAerospace engineeringRotor (electric)AeronauticsLift (data mining)PropulsionMarine engineeringAutomotive engineeringAerodynamicsComputer scienceEngineeringEnvironmental scienceMechanical engineering

Abstract

fetched live from OpenAlex

The CH-53K® King Stallion™ is the most advanced heavy lift helicopter developed by Sikorsky, a Lockheed Martin Company, to address the requirements of the United States Marine Corps. The aircraft was designed to support missions with a maximum design gross weight of 88000 lbs and can carry external loads up to 36000 lb. Full-aircraft HELIOS calculations were performed for a CH-53K King Stallion including main rotor, tail-rotor, fuselage and detailed hub. Calculations were performed for various configurations, with main-rotor removed, tail-rotor removed, and isolated main and tail rotors to evaluate the multiple interactional effects. Comparisons of the total power show excellent agreement with the flight-test measurements.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.205
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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